Combining Automated Lesion Risk and Change Assessment Improves Melanoma Detection: A Retrospective Accuracy Study

. 2025 Mar;145(3):703-706.e1.

doi: 10.1016/j.jid.2024.07.027. Epub 2024 Sep 7.

Affiliations

¹ Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia. Electronic address: c.rutjes@uq.edu.au.
² Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia; Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
³ Canfield Scientific, Parsippany, New Jersey, USA.
⁴ Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia.
⁵ Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia; Dermatology Department, Princess Alexandra Hospital, Brisbane, Australia.
⁶ Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

Chantal Rutjes et al. J Invest Dermatol. 2025 Mar.

. 2025 Mar;145(3):703-706.e1.

doi: 10.1016/j.jid.2024.07.027. Epub 2024 Sep 7.

¹ Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia. Electronic address: c.rutjes@uq.edu.au.
² Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia; Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
³ Canfield Scientific, Parsippany, New Jersey, USA.
⁴ Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia.
⁵ Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia; Dermatology Department, Princess Alexandra Hospital, Brisbane, Australia.
⁶ Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.

No abstract available

Keywords: 3D total-body photography; Artificial intelligence; Melanoma; VECTRA.

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